Objectives

Field sampling

Two distinct locations are being monitored with different historical land-use and management in the province of Aragón (Spain): Ejea de los Caballeros (42º 01’ 06” N, 1º 08’ 53” W) at 350m above sea level with a total of 21 plots and Cantavieja (40º 30’ 44”, N 0º 22’ 59” W) at 1450m with a total of 30 plots. Plot size is 2m by 2m and they are distributed randomly within each location (see Figure x).

Figure 1.

Figure 1.

Data preparation

#Data processing and preparation for visualization and analysis

#First,load libraries
library(dplyr)
library(reshape2)
library(bipartite)

#Read data
data <- read.csv("life_polinizadores.csv")

#check structure of the data
#str(data)

#create separate datasets for the two different locations
ejea <- data %>% filter(site_id=="ejea caballeros")
canta <- data %>% filter(site_id=="cantavieja")

#select for now plant and pollinator species to create plant-pollinator networks from transects
ejea_species <- ejea %>% select(c("plants", "pollinators"))
canta_species <- canta %>% select(c("plants", "pollinators"))

#Now aggregate pollinator visits per plant species
ejea_aggreagted <-  ejea_species %>% count(plants, pollinators, sort = TRUE)
canta_aggreagted <- canta_species %>% count(plants, pollinators, sort = TRUE)

#Now convert to a matrix with the help of acast function from reshape library
ejea_matrix <- acast(ejea_aggreagted, plants~pollinators, value.var="n")
canta_matrix <- acast(canta_aggreagted, plants~pollinators, value.var="n")

#Convert NA's to zeros
ejea_matrix[is.na(ejea_matrix)] <- 0
canta_matrix[is.na(canta_matrix)] <- 0

Data visualization

Location 1 ‘Ejea caballeros’

#Set species names in italic
par(font = 3)

#Plot location 1
plotweb(sortweb(ejea_matrix, sort.order="dec"), method="normal", text.rot=90, 
col.low = "darkolivegreen1", col.high = "darkorange",
col.interaction="gray75",bor.col.interaction ="NA", labsize =.5)

Location 2 ‘Cantavieja’

#Plot location 2
plotweb(sortweb(canta_matrix, sort.order="dec"), method="normal", text.rot=90, col.low = "darkolivegreen1", col.high = "darkorange",col.interaction="gray75",
bor.col.interaction ="NA", labsize =.5)

Analysis of network structure

  1. Analizar y visualizar de forma reproducible las dos parcelas siguiendo, por ejemplo, estos codigos: https://ibartomeus.github.io/hab-sp_ntw/demo.html (Jose y Nacho)